Application of an adaptive filter for criticality surveillance systems

Abstract

Applicability of the adaptive filter for an on-line criticality surveillance system has been discussed through numerical simulations and analysis of real data from a subcritical reactor, based on the fact that the break frequency in the higher frequency region of the PSD of the neutron signal fluctuation has a one-to-one correspondence to subcriticality within the framework of a point reactor kinetics. The recursive extended least squares (RELS) algorithm, a modified RELS algorithm, and the recursive maximum likelihood (RML) algorithm have been examined and it was found that: 1. 1. The model parameters estimated by the adaptive filters do not converge to the theoretical values, however, the PSD of the model agrees well with that of the theoretical one in a higher frequency region. 2. 2. The modified RELS method is best for ARMA model identification of the neutron signal fluctuation from the viewpoint of parameter convergence when the sampling frequency, an anti-aliasing filter and a high-pass filter are appropriately selected. 3. 3. The order of ARMA model is best at (2,2) for subcriticality resolution. 4. 4. The break frequency of the first-order high-pass filter should be set within the range 1/10-1/100 of the break frequency of the PSD of the neutron signal in a higher frequency region. These results indicate that: this approach cannot provide the absolute value of subcriticality without criticality measurement in contrast to Mihalczo's method, however, it can be applicable to an inexpensive on-line monitoring system of reactivity change with a relatively small amount of numerical calculations.